Signal Correlation Modeling in Acoustic Vector Sensor Arrays

Open lake experiment for direction of arrival estimation using acoustic vector sensor array

We examine the improvement attained by using acoustic vector-sensors for direction-of-arrival (DOA) estimation, instead of traditional pressure sensors, via optimal performance bounds and particular estimators. By examining the Cramer-Rao bound in the case of a single source, we show that a vector-sensor array's smaller estimation error is a result of two distinct phenomena: (1) an effective increase in signal-to-noise ratio due to a greater number of measurements of phase delays between sensors and (2) direct measurement of the DOA information contained in the structure of the velocity field due to the vector sensors' directional sensitivity. Separate analysis of these two phenomena allows us to determine the array size, array shape, and SNR conditions under which the use of a vector-sensor array is most advantageous and to quantify that advantage. By extending the beamforming and Capon (1969) direction estimators to vector-sensors, we find that the vector-sensors' directional sensitivity removes all bearing ambiguities. In particular, even simple structures such as linear arrays can determine both azimuth and elevation, and spatially undersampled regularly spaced arrays may be employed to increase the aperture and, hence, the performance. Large sample approximations to the mean-square error matrices of the estimators are derived and their validity is assessed by Monte Carlo simulation.

A two-dimensional (2D) vector sensor measures one acoustic pressure and two acoustic particle velocity components of the acoustic field. In this paper, a new approach is presented for localization of acoustic sources using an array of 2D vector sensors. A simple algorithm for estimating the source location with this array is presented along with their statistical performance analysis. The simulation experiment is presented to verify the efficacy of the proposed localization method and simultaneously analyzing the factors which affects the accuracy of localization.

This paper presents an L-shaped sparsely-distributed vector sensor (SD-VS) array with four different antenna compositions. With the proposed SD-VS array, a novel two-dimensional (2-D) direction of arrival (DOA) and polarization estimation method is proposed to handle the scenario where uncorrelated and coherent sources coexist. The uncorrelated and coherent sources are separated based on the moduli of the eigenvalues. For the uncorrelated sources, coarse estimates are acquired by extracting the DOA information embedded in the steering vectors from estimated array response matrix of the uncorrelated sources, and they serve as coarse references to disambiguate fine estimates with cyclical ambiguity obtained from the spatial phase factors. For the coherent sources, four Hankel matrices are constructed, with which the coherent sources are resolved in a similar way as for the uncorrelated sources. The proposed SD-VS array requires only two collocated antennas for each vector sensor, thus the mutual coupling effects across the collocated antennas are reduced greatly. Moreover, the inter-sensor spacings are allowed beyond a half-wavelength, which results in an extended array aperture. Simulation results demonstrate the effectiveness and favorable performance of the proposed method.

Most underwater target tracking algorithms are based on noisy bearing-only measurements. The bearing measurements are actually bearing estimates obtained from acoustic field measurements made by an array of sensors placed on a manoeuvrable platform. In this paper, we investigate the problem of tracking a manoeuvring target in the ocean directly from the acoustic field measurements. The use of acoustic field measurements eliminates the need for the use of a manoeuvrable platform, and also eliminates the intermediate step of bearing estimation. We consider the vector acoustic field measurements by an array of acoustic vector sensors (AVS), which are more informative than the scalar acoustic field measurements by an array of acoustic pressure sensors (APS). We model the target dynamics by a piecewise-constant turn rate model. The resultant nonlinear estimation problem is solved using the Gaussian approximation filtering approach. Within this framework, we consider the quasi-Monte Carlo Kalman filtering (QMC-KF) algorithm that employs an advanced numerical integration procedure to solve the multi-dimensional integrals appearing in the filtering process. We also derive the posterior Cramer-Rao lower bound (PCRLB) on the root mean square error (RMSE) of the sequential Bayesian estimator, and show that the PCRLB for acoustic field measurements is lower than that for bearing-only measurements. Simulation results indicate that acoustic field measurements yield a significantly better performance than bearing-only measurements, the QMCKF performs better than other deterministic filters, and an AVS array provides a much better performance than an APS array.

In support of monitoring technologies to evaluate the potential environmental effects of offshore energy devices, this project attempts to ultimately improve upon traditional acoustic sensing techniques by developing a cost-effective compact array of acoustic vector sensors that characterizes, classifies, and provides accurate location information for anthropogenic and natural sounds. The NoiseSpotter consists of three acoustic vector sensors arranged in a three-dimensional array deployed as a seafloor mooring. Each vector sensor measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. Here, performance characteristics of the NoiseSpotter are presented, along with an analysis of its abilities as an operational passive acoustic monitoring system to characterize sources of sound. Data are presented from controlled acoustic transmissions in a quiet environment and an energetic tidal channel in the presence of non-acoustic flow noise. NoiseSpotter performance is demonstrated through its modular design, ease of deployment/recovery, ability to remove signal contamination by flow noise and the ability to geolocate acoustic sources of interest.

In this paper, using broadband beamforming sub-array synthesis method carried out theoretical calculations and simulation analysis by a multiple vector-sensor array. The results show that using sub-array synthesis method of constant beam width of the theory is simple and can greatly reduce the computation, while vector sensor array using of broadband constant beamwidth beamforming method are superior to conventional acoustic pressure array in spatial gain, aperture of array and anti-port/starboard ambiguity property etc.

Monopulse based DOA and polarization estimation with polarization sensitive arrays

Signal acquisition and sensing in underwater systems and applications is typically a challenging issue due to the small signal strength within the background noise. Here, we present a ring vector sensor communication receiver that can significantly improve signal acquisition, by utilizing the underwater acoustic vector field components, compared to the scalar component. The vector sensor receiver is a multichannel receiver that measures particle velocities, which are vector components of the underwater acoustic field, in addition to the scalar field component. According to the combination of our measured experimental data with our signal acquisition performance analysis, the introduced ring vector sensor receiver exhibits higher signal acquisition probabilities for the vector components compared to the scalar component. This can be attributed to certain characteristics of the vector field components. Another advantage of this multichannel receiver is that combining all of its channels can further increase the signal acquisition and packet detection probability in underwater communication systems compared to a single-channel approach.

Acoustic data collected from a 22 m long horizontal line array with elements comprised of omni-directional hydrophone sensors co-located with acceleration vector sensor triplets are analyzed for seabed geo-acoustic information. Broadband and continuous wave tone data were recorded from the passage of a surface vessel source, the R/V Montague, in an August 2006 experiment conducted in Monterey Bay. The water depth at the array and along the source track was approximately 85 m. Simultaneous inversions for source track and geo-acoustic parameters were performed with 18 tones from the 62-415 Hz tone data for source ranges 0.5-2.0 km. The efficacy of inversions with vector sensor data is demonstrated by the fact that data from vector sensor acceleration components parallel to the array line of bearing produced inversion solutions approximately identical to the solutions obtained from the inversion of data for the same tones from the hydrophone array components. In addition the source spectra derived from these inversions are in nominal agreement with the source spectra obtained from an independent measurement.

Detection of signals in oceanic waveguides is complex because of uncertainties in the underwater channel and potentially suboptimal location of receiving phones. Accurate detection and estimation are a direct result of optimization with respect to frequency, environmental parameters, and receiver location. We here study the impact of these parameters on detection and propose methods for improvement, including detection processor calibration for optimal performance. We complement our work by investigating detection performance with real data collected at different sensors in a pool. In addition to conventional hydrophones, we also use vector sensors. The rationale behind using a vector sensor is that particle velocity components may show different noise and channel characteristics such as a different number of modes and different dispersive behavior, which are tightly related to detection. We study several detectors and evaluate their performance. [Work supported by ONR and NSF.]

Multipath fading is one of the major practical concerns in wireless communications. A multipath transmission takes place when a transmitted signal arrives at a receiver by two or more paths of different delay. Such multiple paths may be due to atmospheric reflection or refraction, or reflections from buildings or other objects. A multipath fading channel is usually modeled as a time-variant tapped delay system. RAKE receiver can be used to detect the signal from the multipath fading channel. However, the number of delay taps, the time delay of each path, and the tap weight for each delay path need to be determined. The objective of this thesis is to explore the possibility of using the advance signal processing algorithms to estimate the number of delays, the time delay of each path, and the tap weight for each delay path in multipath channels and to investigate the performance of the RAKE receiver based on chip rate channel estimates in a realistic mobile environment. Simulations show that the new approach outperforms the existing approaches.

The industrial scenario is indispensable for ubiquitous 6G coverage, which demands hyper-reliable and low-latency communication for full automation, control, and operation. To meet these demands, it is widely believed that it is necessary to introduce not only the conventional sub-6 GHz bands but also high-frequency technologies, such as millimeter wave (mmWave), terahertz (THz), and visible light bands. In this paper, we conduct a channel characterization and comparison in the industrial scenario from the sub-6 GHz to visible light bands. The channel characteristics, including the path loss (PL), root mean square (RMS) delay spread (DS), and angle spread (AS), were analyzed with respect to the frequency dependence and the distance dependence. On the one hand, the visible light band exhibited significant differences in channel characteristics compared to the electronic wave band. Due to the line-of-sight transmission of VLC, the visible light band had a higher path loss, and the path loss exponent reached 3.84. Due to the Lambertian radiation pattern, which has a wide range of reflection angles, the AS of the visible light band was much larger than that of the electronic wave band, which were 1.73 and 0.80 for the visible light and THz bands, respectively. On the other hand, the blockage effect of the metal instruments in the industrial scenario will greatly affect the channel characteristics. As the transceiver distance grows large, signals from both sides of the receiver will be blocked by metal instruments, resulting in a decreasing trend in the RMS DS for the electronic wave band. Moreover, the statistical characteristics of the channel properties were modeled and compared with the 3GPP TR 38.901 standard. It was found that the height of the receiver caused the difference between the proposed model and the 3GPP model and needs to be taken into account when modeling. Furthermore, we extended the 3GPP model to the THz and VLC bands and provided the statistical parameters of the channel characteristics for all frequency bands. This study can provide insights for the evaluation and standardization of multi-frequency communication technology in the industrial scenario.

Underwater acoustic communication to an unmanned underwater vehicle with a compact vector sensor array

A hybrid acoustic vector sensor array (HAVSA) is consisted mainly of pressure hydrophones and a few vector sensors within. It can acquire good direction-finding results as well as the ability to discriminate the left-right ambiguity at a considerably low cost, and thus is regarded as a promising novel array configuration. In this paper we have deduced the formula of the directivity of HAVSA, and analyzed its characteristics. Results showed that factors, such as the number and positions of vector sensors utilized in HAVSA, the steering angle, and the signal frequency will change the main lobe width, the height of the side lobes, and the left-right ambiguity elimination performance of the array. Furthermore, the general processing method of the HAVSA for DOA estimation is presented, and conventional beamforming (CBF) and Capon beamforming methods are applied. Results show that the HAVSA has the ability to suppress the left-right ambiguity, and the Capon beamforming outperforms CBF. The present work can provide a good reference for the configuration designing and the algorithm researching of HAVSA.